SUMMARY (See instructions): We are witnessing a fundamental transition in biomedical research from a science focused on the function of single molecules or pathways to an information rich discovery science analyzing biological systems and their behavior on a genome-wide level. In clinical sciences, a parallel shift allows to define clinical phenotypes of patients with unprecedented granularity. These two developments provide an opportunity to redefine human disease moving from a phenotypic disease classification to a mechanism-based disease definitions. The primary goal ofthe ASBC is to provide a platform for integrative data mining of genome wide renal disease data sets. The team of the ASCB has developed a unique set of tools and skills to serve as a bridge to connect the deep biological and clinical knowledge ofthe domain experts in the O'Brien Research base with the relevant segments in large-scale molecular and clinical data sets. This goal will be reached by assisting center investigators in integrating rich genetic and molecular data sets generated from C-PROBE and additional cohorts in their focused, hypothesis driven research. The ASBC will thereby facilitate the link of human disease mechanisms to the investigation by our local basic science research base in a bedside-to-bench approach. Conversely, molecular mechanism defined in model systems by the research base will be tested for their human disease relevance. The ASBC will employ individualized search strategies using a suite of data mining tools compiled in a web-based portal system. Interactive shared data-mining will be performed by a systems biologist-biomedical/clinician scientist research team. In addition, experienced center investigators will have the option to use standardized workflows for large-scale data sets of renal disease for semi-supervised data mining. Finally, the global research community will be served by a fully-automated web-based systems biology search engine (Nephromine) for context specific renal disease gene expression data mining. Structured supervision ofthe interaction process will ensure optimal implementation ofthe data-mining infrastructure. The ASBC will facilitate interrogation of novel basic science paradigms in specific human disease processes. Conversely, molecular profiling ofthe patient cohorts will allow definition ofthe underlying molecular mechanisms active in specific renal disease phenotypes for further experimental study. The ASBC will serve as a bi-directional translational machine driving interactions between basic and clinical scientists towards the rapid discovery and implementation of novel therapies for renal disease.